Project Summary/Abstract Chronic pain is a significant and costly public health concern, resulting in a national economic burden of $300 billion annually. Biomarkers identifying those at risk for developing chronic pain are largely unknown. Primary dysmenorrhea (PD), defined as menstrual pain without an identified organic cause, is a unique population for studying pain processes, as women with PD have repeated, defined episodes of pain and are otherwise pain-free. Data suggest that women with PD share similar pain biomarkers with individuals with chronic pain, including enhanced pain sensitivity. Because PD begins in adolescence ? a critical developmental phase associated with establishing neural pathways and refining brain network connectivity ? prospectively identifying alterations in endogenous pain processing and brain structure and connectivity in this population can provide critical information about mechanisms involved in the chronification of pain. This is the crucial next step to designing targeted, individualized treatments to prevent those at risk from developing ongoing pain and disability. The proposed study will use PD as a model to examine biomarkers associated with menstrual and non- menstrual bodily pain in adolescent girls, ages 14-18, who will undergo extensive phenotyping including pain inhibition testing and multimodal neuroimaging to obtain indices of gray matter morphometry, microstructural integrity of white matter, and anatomical (diffusion tensor imaging) and functional (resting state magnetic resonance imaging) connectivity at baseline and 12 months later. Menstrual pain severity and non-menstrual bodily pain will be assessed monthly for 24 months. We aim to 1) identify the central mechanisms of PD using measures of pain inhibition and brain structure and connectivity of sensorimotor, default, emotional arousal, and salience networks, 2) determine deficits in pain inhibition and alterations in brain structure and network connectivity that predict the one-year developmental trajectories of menstrual pain and non-menstrual bodily pain, and 3) identify the dynamic relationship between alterations in pain inhibition and brain structure and connectivity with symptom change in menstrual pain and non-menstrual bodily pain. We hypothesize that deficits in endogenous pain inhibition and alterations in brain structure, connectivity, and function of regional networks will be positively associated with menstrual pain severity ratings at baseline and predict the trajectory of menstrual and non-menstrual bodily pain over 2 years. Imaging data will be analyzed using graph theoretical approaches, and comprehensive data analyses general linear and general linear mixed models. The results are expected to identify specific mechanisms and characteristics that predict the transition from acute/cyclical pain to persistent or chronic pain, which will support the development of therapies, such as cognitive-behavior therapy or transcranial direct current stimulation, to prevent the transition from recurrent to chronic pain in adulthood.